library(hrbrthemes)
library(kableExtra)
options(knitr.table.format = "html")
library(babynames)
# devtools::install_github("hrbrmstr/streamgraph")
library(streamgraph)
library(viridis)
library(DT)
library(plotly)

# Load dataset from github
data <- babynames %>%
  filter(name %in% c("Mary","Emma", "Ida", "Ashley", "Amanda", "Jessica",    "Patricia", "Linda", "Deborah",   "Dorothy", "Betty", "Helen")) %>%
  filter(sex=="F")

# Plot
data %>%
  ggplot( aes(x=year, y=n, group=name, color=name)) +
    geom_line() +
    scale_color_viridis(discrete = TRUE) +
    theme(
      legend.position="none",
      plot.title = element_text(size=14)
    ) +
    ggtitle("A spaghetti chart of baby names popularity")

data %>%
  mutate( highlight=ifelse(name=="Amanda", "Amanda", "Other")) %>%
  ggplot( aes(x=year, y=n, group=name, color=highlight, size=highlight)) +
    geom_line() +
    scale_color_manual(values = c("#69b3a2", "lightgrey")) +
    scale_size_manual(values=c(1.5,0.2)) +
    theme(legend.position="none") +
    ggtitle("Popularity of American names in the previous 30 years") +
    geom_label( x=1990, y=55000, label="Amanda reached 3550\nbabies in 1970", size=4, color="#69b3a2") +
    theme(
      legend.position="none",
      plot.title = element_text(size=14)
)

data %>%
  ggplot( aes(x=year, y=n, group=name, fill=name)) +
    geom_area() +
    scale_fill_viridis(discrete = TRUE) +
    theme(legend.position="none") +
    ggtitle("Popularity of American names in the previous 30 years") +
    theme_ipsum() +
    theme(
      legend.position="none",
      panel.spacing = unit(0.1, "lines"),
      strip.text.x = element_text(size = 8),
      plot.title = element_text(size=14)
    ) +
    facet_wrap(~name)

tmp <- data %>%
  mutate(name2=name)

tmp %>%
  ggplot( aes(x=year, y=n)) +
    geom_line( data=tmp %>% dplyr::select(-name), aes(group=name2), color="grey", size=0.5, alpha=0.5) +
    geom_line( aes(color=name), color="#69b3a2", size=1.2 )+
    scale_color_viridis(discrete = TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none",
      plot.title = element_text(size=14),
      panel.grid = element_blank()
    ) +
    ggtitle("A spaghetti chart of baby names popularity") +
    facet_wrap(~name)

# Libraries
library(tidyverse)
library(hrbrthemes)
library(viridis)
library(plotly)

# create a dataset
data <- data.frame(
  name=c( rep("A",500), rep("B",500), rep("B",500), rep("C",20), rep('D', 100)  ),
  value=c( rnorm(500, 10, 5), rnorm(500, 13, 1), rnorm(500, 18, 1), rnorm(20, 25, 4), rnorm(100, 12, 1) )
)

# Plot
data %>%
  ggplot( aes(x=name, y=value, fill=name)) +
    geom_boxplot() +
    scale_fill_viridis(discrete = TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none",
      plot.title = element_text(size=11)
    ) +
    ggtitle("A somewhat misleading boxplot") +
    xlab("")

data %>%
  ggplot( aes(x=name, y=value, fill=name)) +
    geom_boxplot() +
    scale_fill_viridis(discrete = TRUE) +
    geom_jitter(color="grey", size=0.7, alpha=0.5) +
    theme_ipsum() +
    theme(
      legend.position="none",
      plot.title = element_text(size=11)
    ) +
    ggtitle("A boxplot with jitter") +
    xlab("")

# sample size
sample_size = data %>% group_by(name) %>% summarize(num=n())

# Plot
data %>%
  left_join(sample_size) %>%
  mutate(myaxis = paste0(name, "\n", "n=", num)) %>%
  ggplot( aes(x=myaxis, y=value, fill=name)) +
    geom_violin(width=1.4) +
    geom_boxplot(width=0.1, color="grey", alpha=0.2) +
    scale_fill_viridis(discrete = TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none",
      plot.title = element_text(size=11)
    ) +
    ggtitle("A violin plot") +
    xlab("")

library(ggplot2)
library(ggdist)
library(hrbrthemes)
library(dplyr)
library(viridis)

# Plot
data %>%
  ggplot(aes(x = factor(name), y = value, fill = factor(name))) +
  
  # Add half-violin from {ggdist} package
  stat_halfeye(
    adjust = 0.5,
    justification = -0.2,
    .width = 0,
    point_colour = NA
  ) +
  
  geom_boxplot(
    width = 0.12,
    outlier.color = NA,
    alpha = 0.5
  ) +
  
  stat_dots(
    side = "left",
    justification = 1.1,
    binwidth = 0.25
  ) +
  
  scale_fill_viridis(discrete = TRUE) +
  theme_ipsum() +
  theme(
    legend.position = "none",
    plot.title = element_text(size = 11)
  ) +
  ggtitle("A raincloud plot example") +
  xlab("")

#library
library(tidyverse)
library(hrbrthemes)
library(viridis)
library(patchwork)


# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/zonination/perceptions/master/probly.csv", header=TRUE, sep=",")
data <- data %>%
  gather(key="text", value="value") %>%
  mutate(text = gsub("\\.", " ",text)) %>%
  mutate(value = round(as.numeric(value),0))

data %>%
  mutate(text = fct_reorder(text, value)) %>%
  ggplot( aes(x=value, color=text, fill=text)) +
    geom_density(alpha=0.6) +
    scale_fill_viridis(discrete=TRUE) +
    scale_color_viridis(discrete=TRUE) +
    theme_ipsum() +
    theme(
      panel.spacing = unit(0.1, "lines"),
      strip.text.x = element_text(size = 8)
    ) +
    xlab("") +
    ylab("Assigned Probability (%)")

data %>%
  mutate(text = fct_reorder(text, value)) %>%
  ggplot( aes(x=text, y=value, fill=text)) +
    geom_boxplot() +
    geom_jitter(color="grey", alpha=0.3, size=0.9) +
    scale_fill_viridis(discrete=TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none"
    ) +
    coord_flip() +
    xlab("") +
    ylab("Assigned Probability (%)") 

data %>%
  mutate(text = fct_reorder(text, value)) %>%
  ggplot( aes(x=text, y=value, fill=text, color=text)) +
    geom_violin(width=2.1, size=0.2) +
    scale_fill_viridis(discrete=TRUE) +
    scale_color_viridis(discrete=TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none"
    ) +
    coord_flip() +
    xlab("") +
    ylab("Assigned Probability (%)")

library(ggridges)
data %>%
  mutate(text = fct_reorder(text, value)) %>%
  ggplot( aes(y=text, x=value,  fill=text)) +
    geom_density_ridges(alpha=0.6, bandwidth=4) +
    scale_fill_viridis(discrete=TRUE) +
    scale_color_viridis(discrete=TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none",
      panel.spacing = unit(0.1, "lines"),
      strip.text.x = element_text(size = 8)
    ) +
    xlab("") +
    ylab("Assigned Probability (%)")

data %>%
  mutate(text = fct_reorder(text, value)) %>%
  ggplot( aes(x=value, color=text, fill=text)) +
    geom_density(alpha=0.6) +
    scale_fill_viridis(discrete=TRUE) +
    scale_color_viridis(discrete=TRUE) +
    theme_ipsum() +
    theme(
      legend.position="none",
      panel.spacing = unit(0.1, "lines"),
      strip.text.x = element_text(size = 8)
    ) +
    xlab("") +
    ylab("Assigned Probability (%)") +
    facet_wrap(~text, scale="free_y")

# Libraries
library(tidyverse)
library(hrbrthemes)
library(viridis)
library(patchwork)

# Dataset:
a <- data.frame( x=rnorm(20000, 10, 1.2), y=rnorm(20000, 10, 1.2), group=rep("A",20000))
b <- data.frame( x=rnorm(20000, 14.5, 1.2), y=rnorm(20000, 14.5, 1.2), group=rep("B",20000))
c <- data.frame( x=rnorm(20000, 9.5, 1.5), y=rnorm(20000, 15.5, 1.5), group=rep("C",20000))
data <- do.call(rbind, list(a,b,c))

data %>%
  ggplot( aes(x=x, y=y)) +
    geom_point(color="#69b3a2", size=2) +
    theme_ipsum() +
    theme(
      legend.position="none"
    )

# Plot with small dot size
data %>%
  ggplot( aes(x=x, y=y)) +
    geom_point(color="#69b3a2", size=0.02) +
    theme_ipsum() +
    theme(
      legend.position="none"
    )

# Plot with small dot size
data %>%
  ggplot( aes(x=x, y=y, color=group)) +
    geom_point( size=2, alpha=0.1) +
    scale_color_viridis(discrete=TRUE) +
    theme_ipsum()

ggplot(data, aes(x=x, y=y) ) +
  stat_density_2d(aes(fill = ..density..), geom = "raster", contour = FALSE) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0)) +
  scale_fill_viridis() +
  theme(
    legend.position='none'
  )

library(plotly)
library(MASS)

# Compute kde2d
kd <- with(data, MASS::kde2d(x, y, n = 50))

# Plot with plotly
plot_ly(x = kd$x, y = kd$y, z = kd$z) %>% add_surface()